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Global Physical Climatology, Volume 56 (International Geophysics)

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Global Physical Climatology is an introductory text devoted to the fundamental physical principles and problems of climate sensitivity and change. Addressing some of the most critical issues in climatology, this text features incisive coverage of topics that are central to understanding orbital parameter theory for past climate changes, and for anthropogenic and natural causes of near-future changes– Key Features* Covers the physics of climate change* Ex…

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[AMA Request] A Scientist Who Does Not Believe Climate Change is Real and/or Human Caused.(r/IAmA)

I’m a climate scientist. All four of your problems have very straightforward answers – which I’ll quickly provide at the end of this comment – but they ignore the most important aspect of climate change science: we understand the physics of the climate system. Our knowledge about climate change doesn’t come directly from the data; Arrhenius certainly didn’t have that data when he put forth the hypothesis that CO2 in the Earth’s atmosphere could contribute to global temperature levels back in 1896, and Guy Callendar didn’t have that data when he developed the first model of the planetary atmospheric greenhouse effect in the 1920’s and 1930’s. We first had theory deriving from physics and thermodynamics, which made robust predictions about what data we should collect. When we’ve collected that data over the past 60 years, it almost always re-affirms the theory which underpins it. And when it doesn’t, we learn new things to incorporate into our understanding of the climate system.

That’s the primary difference between your background as a statistics/finance/econ guy and my background as a scientist. Data does not define theory in my world. Theory and data work together to build knowledge in an iterative cycle. You cannot ignore data and you cannot ignore theory. And you cannot assume that one is right versus the other.

That said, to your points:

“Linear” has nothing to do with your example, which mixes apples and oranges. You have to convert your GDP data to different bases because the metrics you use change over time. In the science world, the data we have is constrained by physics, and that provides a simple, universal way to interpret it.

You interpret the data by comparing to theory. If you’re not familiar with the theory, then you can’t possibly be in a position to evaluate how the data is being interpreted, which leads to…

You become a scientist. You study the physics and dynamics of the climate system, using books like this, this, this, and this. And that’s just what you’d learn in your first semester of graduate school in the field!

Virtually all of the data you could possibly want about climate is freely accessible. All of the science is readily available, too, since scientists base their entire careers on publishing their methods and results for the peers to review. Seriously – what data can you not access? What equation can you not find?

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